Jiaqiang Luo, Jamie Selby-Pham, Kimber Wise, Yinhao Wu, Jiacan Sun, Yameng Qu, Tian Cao, Pangzhen Zhang, Philip J. Marriott, Kate Howell
{"title":"基于葡萄中微量挥发性化合物的设拉子葡萄酒品质早期预测","authors":"Jiaqiang Luo, Jamie Selby-Pham, Kimber Wise, Yinhao Wu, Jiacan Sun, Yameng Qu, Tian Cao, Pangzhen Zhang, Philip J. Marriott, Kate Howell","doi":"10.1155/2023/2990963","DOIUrl":null,"url":null,"abstract":"Wine producers perform early wine quality prediction based on berry morphology, the taste of the berry and the measurement of basic chemical parameters. Incorporating analysis on grape and wine volatiles could potentially achieve a more accurate prediction of wine quality, but forming these models requires careful selection of grapes, controlled fermentations, and standardised quality assessment. Here, we present 3 models for the prediction of quality in Shiraz wine. Modelling was performed by general regression analysis with 4-fold cross-validation: Model 1 (R2 = 99.97% and 4-foldR2 = 97.61%) for prediction of wine quality from wine volatiles, Model 2 (R2 = 99.89% and 4-foldR2 = 98.42%) for early prediction of wine quality from free-bound and glycosidically bound grape volatiles, and Model 3 (R2 = 91.62% and 4-foldR2 = 80.21%) for the prediction of wine quality from free grape volatiles only. The accuracy of these models presents an advancement in the early prediction of wine quality and provides a valuable tool to assist grape growers and winemakers to support the understanding of quality in the vineyard to better direct scarce resources.","PeriodicalId":8582,"journal":{"name":"Australian Journal of Grape and Wine Research","volume":"18 1","pages":"0"},"PeriodicalIF":2.5000,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Early Prediction of Shiraz Wine Quality Based on Small Volatile Compounds in Grapes\",\"authors\":\"Jiaqiang Luo, Jamie Selby-Pham, Kimber Wise, Yinhao Wu, Jiacan Sun, Yameng Qu, Tian Cao, Pangzhen Zhang, Philip J. Marriott, Kate Howell\",\"doi\":\"10.1155/2023/2990963\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wine producers perform early wine quality prediction based on berry morphology, the taste of the berry and the measurement of basic chemical parameters. Incorporating analysis on grape and wine volatiles could potentially achieve a more accurate prediction of wine quality, but forming these models requires careful selection of grapes, controlled fermentations, and standardised quality assessment. Here, we present 3 models for the prediction of quality in Shiraz wine. Modelling was performed by general regression analysis with 4-fold cross-validation: Model 1 (R2 = 99.97% and 4-foldR2 = 97.61%) for prediction of wine quality from wine volatiles, Model 2 (R2 = 99.89% and 4-foldR2 = 98.42%) for early prediction of wine quality from free-bound and glycosidically bound grape volatiles, and Model 3 (R2 = 91.62% and 4-foldR2 = 80.21%) for the prediction of wine quality from free grape volatiles only. The accuracy of these models presents an advancement in the early prediction of wine quality and provides a valuable tool to assist grape growers and winemakers to support the understanding of quality in the vineyard to better direct scarce resources.\",\"PeriodicalId\":8582,\"journal\":{\"name\":\"Australian Journal of Grape and Wine Research\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2023-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Australian Journal of Grape and Wine Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2023/2990963\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Australian Journal of Grape and Wine Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2023/2990963","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Early Prediction of Shiraz Wine Quality Based on Small Volatile Compounds in Grapes
Wine producers perform early wine quality prediction based on berry morphology, the taste of the berry and the measurement of basic chemical parameters. Incorporating analysis on grape and wine volatiles could potentially achieve a more accurate prediction of wine quality, but forming these models requires careful selection of grapes, controlled fermentations, and standardised quality assessment. Here, we present 3 models for the prediction of quality in Shiraz wine. Modelling was performed by general regression analysis with 4-fold cross-validation: Model 1 (R2 = 99.97% and 4-foldR2 = 97.61%) for prediction of wine quality from wine volatiles, Model 2 (R2 = 99.89% and 4-foldR2 = 98.42%) for early prediction of wine quality from free-bound and glycosidically bound grape volatiles, and Model 3 (R2 = 91.62% and 4-foldR2 = 80.21%) for the prediction of wine quality from free grape volatiles only. The accuracy of these models presents an advancement in the early prediction of wine quality and provides a valuable tool to assist grape growers and winemakers to support the understanding of quality in the vineyard to better direct scarce resources.
期刊介绍:
The Australian Journal of Grape and Wine Research provides a forum for the exchange of information about new and significant research in viticulture, oenology and related fields, and aims to promote these disciplines throughout the world. The Journal publishes results from original research in all areas of viticulture and oenology. This includes issues relating to wine, table and drying grape production; grapevine and rootstock biology, genetics, diseases and improvement; viticultural practices; juice and wine production technologies; vine and wine microbiology; quality effects of processing, packaging and inputs; wine chemistry; sensory science and consumer preferences; and environmental impacts of grape and wine production. Research related to other fermented or distilled beverages may also be considered. In addition to full-length research papers and review articles, short research or technical papers presenting new and highly topical information derived from a complete study (i.e. not preliminary data) may also be published. Special features and supplementary issues comprising the proceedings of workshops and conferences will appear periodically.